Speech recognition and transcription AI built on self-trained neural models
Speechmatics develops automatic speech recognition models and sells them as transcription and speech-understanding APIs. Its stack pairs PyTorch, TensorFlow and Flash Attention with Kubernetes, Terraform, ArgoCD and GitOps across AWS, Azure and GCP, which points to in-house large-model training rather than reliance on third-party models. Hiring is accelerating and engineering-heavy, centred on senior and principal ML and infrastructure talent.
Speechmatics is a Cambridge, UK-based speech technology company founded in 2006, with an additional office in New York. It builds machine learning models that convert spoken audio into text, both in real time and from recorded media, across many languages and accents. Businesses build products on top of these transcripts, adding capabilities such as summaries, sentiment, topics and translation. The privately held company has 51–200 employees and hires in the United Kingdom, the United States and Serbia.
Speechmatics uses Python, PyTorch, TensorFlow and Flash Attention for ML, with Kubernetes, Docker, Terraform, Helm and ArgoCD on AWS, Azure and GCP. React, TypeScript and SvelteKit cover the front end.
Yes. Hiring is accelerating and mostly in engineering, skewed toward senior, lead and principal roles, with some sales hiring, across the United Kingdom, the United States and Serbia.
Job posts point to training large self-supervised speech models, deploying them into production, building scalable training-data pipelines and building model deployment and evaluation infrastructure.
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Speechmatics's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
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